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Operation Scenario Tool

SE-tool for operation scenario analysis

Directory

operation-scneario             #  運用シナリオ解析
├─ docs                        #  関連メモ (削除するかも)
│   
├─ csv                         # 運用シナリオ情報 (CSV): 結果がここに出力される
│   
├─ json                        # 設計情報管理
│   ├─ components              # コンポーネント情報 (Ex: 製品名, 電力, 熱特性, 重量)
│   │   
│   ├─ operation-scenario      # 運用シナリオ (現在はまだ使用されていない.)
│   │   
│   ├─ operation_mode          # 運用 (電源) モード (Ex:　機器動作モード)
│   │   
│   ├─ orbit                   # 軌道情報
│   │   
│   └─ spacecraft              # 宇宙機情報
│   
├─ notebook                    # 解析Jupyter Notebookファイル
│   └─ test_analysis.ipynb     # 試験用解析
│   
├─ src                         # 解析用モジュール
│   ├─ db_loader.py            # データベース読み込みクラス
│   │   
│   └─ operation_scenario.py   # 運用シナリオ解析クラス
│   
├─ README.md                   # 
└─ requirements.txt            #

How To Use (User)

1. Install required packages

pip3 install -r requirements.txt

If you want to make a local environment, use venv package

python3 -m venv venv
. venv/bin/activate
pip3 install -r requirements.txt

2. Edit the json files if needed

We recommend to use the json_editor. By uploading the schema files, you can edit json files using a GUI.

File Name Description
json/components/(Subsystem)_(ComponentName).json json files for components
json/components/component_schema.json json schema for components
json/operation_mode/(MissionName)/(Mode_Name).json json files for operation (power) mode. Defined for each mission
json/operation_mode/(MissionName)/_Mode2Pointing.json json file that assigns pointing direction for each operation mode.
json/spacecraft/(SpacecraftName).json json file for spacecraft configurations.

3. Write and run the notebook file for operation scenario analysis

Refer to test_analysis.ipynb for examples.

Flow of Analysis

Basic flows for writing jupyter notebook analysis files are shown below.

Step1. Define mission name and load json files using DBLoader.

json_basedir = '../json'
spacecraft_name = "NSPO"
db_loader = DBLoader(json_basedir, spacecraft_name)

Step2: Define operation scenario parameters (Ex: orbit parameters) and initialize OperationScenario Class.

mode2pointing_file = os.path.join(json_basedir,"operation_mode","NSPO","_Mode2Pointing.json")
mode2pointing = json.load(open(mode2pointing_file,"r"))
ops = OperationSceneario(altitude=400, beta=72/180*np.pi, t0_sun_ratio=0, pass_time_average=400, 
                         mode2pointing=mode2pointing, dt=30)

Step3: Assign baseline opration Modes

ops.alloc_operation_mode_to_ecp_type([2,3], 'Eclipse')
ops.alloc_operation_mode_to_ecp_type([0,1], 'AOCS_Keeping_Sun_Pointing')

Step4: Overwrite operation mode using trigger functions

operaion_modes = ["AOCS_Unloading"]
durations = [1800]
trigger_ecp_type = 1  # sun + non-pass
shift_t = 540
ops.alloc_operation_modes_by_ecp_type_trigger(operation_modes=operaion_modes, durations=durations,
                                              trigger_ecp_type=trigger_ecp_type,
                                              shift_t=shift_t)

Step5: Run calculation

ops.run(db_loader.sp_dict)

Step6: Postprocessing
There are example of visualizing generated power transition and eclipse/pass trainsition in json/testanalysis.ipynb
You can output the operation dataframe to a csv file using the following function

ops.dataframe.to_csv("../csv/(Filename).csv")